AI's Impact on Data Provenance
April 29, 2024

Blane Sims
Truebit

As organizations increasingly harness artificial intelligence (AI) to power various functions, the integrity, security, and reliability of the data inputted into these systems become paramount. This approach is fundamental in avoiding pitfalls during model training, a challenge commonly recognized by AI developers. There is still a trust deficit when companies are not clear about the origin, lineage and rights associated with the data that feeds their systems.

Blockchain and Web3 represent the ideal environment for hosting neutral AI. By anchoring the training data, models, and AI utilization on blockchains, we gain visibility into data origins and decision-making processes. This transparency enables the enforcement of fair content usage for generative AI, ensuring trustworthy payouts to content owners and creators.

With distributed ledgers, blockchains offer an indisputable level of transparency and provenance. No single player owns a truly decentralized blockchain. Independent parties keep their own copies of every transaction, ensuring that data origins are traceable and immutable. This cryptographic security, coupled with consensus mechanisms, guarantees the integrity of data, making blockchains an ideal platform for securing neutral AI applications.

While blockchains back the data security of neutral AI, decentralized Web3 compute networks provide the force. Decentralization creates an open market of servers, GPUs, and storage that are available on demand to train and run AI. The code portability required for decentralization creates strong incentives around open source AI frameworks instead of the proprietary toolkits favored by tech giants. This open market also provides a rational basis for anyone who owns compute resources — be it a cloud provider, a startup, a university, or a public consortium — to power neutral AI by removing the economic benefit of hoarding those resources.

The biggest Web3 innovation that will foster neutral AI, though, is transparent governance. Transparent governance, as expressed through smart contracts and other forms of verifiable code, provides clear rules and kill switches that align with our consensus as a society about what we want AI to do for us. The ability to get paid when AI uses content you create can be automatically enforced across any derivative works. Biases and blindspots can be permanently eradicated by enforcement of coding and training data requirements. And all of these rules can be continuously, publicly audited for compliance.

Web3 has the power to make AI trustworthy and neutral, and the technology is moving fast to fill this need. Web3 skeptics previously pointed to scalability, data privacy, and environmental impact as obstacles to adoption. A new generation of blockchains and a vastly expanded Web3 technology stack are closing these gaps. This sets Web3 up to become a key part of the emerging infrastructure for AI, and further advances in Web3 will require investment orders of magnitude smaller than the astronomic cost of buying GPU chips.

Verified compute stands out as the capability that unlocks the potential to create neutral AI. Verified compute allows networks of independently owned computers to operate securely and transparently. Whereas blockchains provide the ledger to record the audit trail of a decentralized network, verified compute makes it safe to send the AI training jobs and model inference requests to servers you don't control. Verification makes it possible to observe the code, inputs and outputs of an AI compute task and provides immutable proof of correctness.

This ability to auditably run any code anywhere also serves as a platform for transparent governance. The complex code needed to independently track training data across innumerable sources, and enforce AI safety can be reliably run on a verified compute network without any one party holding dictatorial control. This approach ensures that AI applications remain unbiased, transparent, and verifiable, fostering trust and integrity in digital ecosystems.

As we wrestle with the question of how to lay the groundwork for these profound changes without sowing seeds of destruction, we must move deliberately toward a level playing field. Web3 allows us to pool resources, collaborate on the development of underlying technology, and fairly compensate for the real human work that makes AI possible. When rationally weighed against a model where only a handful of players invest trillions of dollars to "win it all," Web3-driven AI is the fastest path to the most gain for everyone.

Blane Sims is Head of Product at Truebit
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